Efficient Federated Meta-Learning Over Multi-Access Wireless Networks
IEEE Journal on Selected Areas in Communications(2022)
摘要
Federated meta-learning (FML) has emerged as a promising paradigm to cope with the data limitation and heterogeneity challenges in today’s edge learning arena. However, its performance is often limited by slow convergence and corresponding low communication efficiency. In addition, since the available radio spectrum and IoT devices’ energy capacity are usually insufficient, it is crucial to contro...
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关键词
Convergence,Resource management,Training,Internet of Things,Collaborative work,Stochastic processes,Servers
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